ArticleModern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc2020
A novel prognostic two-gene signature for triple negative breast cancer.
Article in Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Stromal transcriptomics uncover LIF as a key effector in high tumor budding triple-negative breast cancer.Scientific reports · 2025Article
- Machine Learning-Based Prognostic Gene Signature for Early Triple-Negative Breast Cancer.Cancer research and treatment · 2025Article
- Improving platelet-RNA-based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification.Molecular oncology · 2024Article
- SPDYC serves as a prognostic biomarker related to lipid metabolism and the immune microenvironment in breast cancer.Immunologic research · 2024Article
- Oncogenic ACSM6 impairs CD8Biomarker research · 2024Article
- The role of the ALKBH5 RNA demethylase in invasive breast cancer.Discover oncology · 2024Article
- Sequence Alignment betweenJournal of personalized medicine · 2024Article
- Artificial intelligence: opportunities and challenges in the clinical applications of triple-negative breast cancer.British journal of cancer · 2023Review
- Application of single-cell RNA sequencing analysis of novel breast cancer phenotypes based on the activation of ferroptosis-related genes.Functional & integrative genomics · 2023Article
- ACSM6 overexpression indicates a non-inflammatory tumor microenvironment and predicts treatment response in bladder cancer: results from multiple real-world cohorts.Frontiers in pharmacology · 2023Article
- Immunohistochemical Overexpression of Cyclin D1 in Tunisian Invasive Breast Carcinoma Women.Archives of Iranian medicine · 2022Article
- High Expression of RAI14 in Triple-Negative Breast Cancer Participates in Immune Recruitment and Implies Poor Prognosis Through Bioinformatics Analyses.Frontiers in pharmacology · 2022Article
- A Novel Prognostic Four-Gene Signature of Breast Cancer Identified by Integrated Bioinformatics Analysis.Disease markers · 2022Article
- Integrating whole genome sequencing, methylation, gene expression, topological associated domain information in regulatory mutation prediction: A study of follicular lymphoma.Computational and structural biotechnology journal · 2022Article
- A network approach reveals driver genes associated with survival of patients with triple-negative breast cancer.iScience · 2021Article
- Review
- Identification and Complete Validation of Prognostic Gene Signatures for Human Papillomavirus-Associated Cancers: Integrated Approach Covering Different Anatomical Locations.Journal of virology · 2021Article
- Development and external validation of a composite immune-clinical prognostic model associated with EGFR mutation in East-Asian patients with lung adenocarcinoma.Therapeutic advances in medical oncology · 2021Article
- Genome Instability-Derived Genes Are Novel Prognostic Biomarkers for Triple-Negative Breast Cancer.Frontiers in cell and developmental biology · 2021Article
- A Novel Seven Gene Signature-Based Prognostic Model to Predict Distant Metastasis of Lymph Node-Negative Triple-Negative Breast Cancer.Frontiers in oncology · 2021Article
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Authors and funding
17 authors.
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Abstract
The absence of a robust risk stratification tool for triple negative breast cancer (TNBC) underlies imprecise and nonselective treatment of these patients with cytotoxic chemotherapy. This study aimed to interrogate transcriptomes of TNBC resected samples using next generation sequencing to identify novel biomarkers associated with disease outcomes. A subset of cases (n = 112) from a large, well-characterized cohort of primary TNBC (n = 333) were subjected to RNA-sequencing. Reads were aligned to the human reference genome (GRCH38.83) using the STAR aligner and gene expression quantified using HTSEQ. We identified genes associated with distant metastasis-free survival and breast cancer-specific survival by applying supervised artificial neural network analysis with gene selection to the RNA-sequencing data. The prognostic ability of these genes was validated using the Breast Cancer Gene-Expression Miner v4. 0 and Genotype 2 outcome datasets. Multivariate Cox regression analysis identified a prognostic gene signature that was independently associated with poor prognosis. Finally, we corroborated our results from the two-gene prognostic signature by their protein expression using immunohistochemistry. Artificial neural network identified two gene panels that strongly predicted distant metastasis-free survival and breast cancer-specific survival. Univariate Cox regression analysis of 21 genes common to both panels revealed that the expression level of eight genes was independently associated with poor prognosis (p < 0.05). Adjusting for clinicopathological factors including patient's age, grade, nodal stage, tumor size, and lymphovascular invasion using multivariate Cox regression analysis yielded a two-gene prognostic signature (ACSM4 and SPDYC), which was associated with poor prognosis (p < 0.05) independent of other prognostic variables. We validated the protein expression of these two genes, and it was significantly associated with patient outcome in both independent and combined manner (p < 0.05). Our study identifies a prognostic gene signature that can predict prognosis in TNBC patients and could potentially be used to guide the clinical management of TNBC patients.
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